HuggingFace Datasets

Datasets and evaluation metrics for natural language processing

Compatible with NumPy, Pandas, PyTorch and TensorFlow

🤗 Datasets is a lightweight and extensible library to easily share and access datasets and evaluation metrics for Natural Language Processing (NLP).

🤗 Datasets has many interesting features (beside easy sharing and accessing datasets/metrics):

  • Built-in interoperability with Numpy, Pandas, PyTorch and Tensorflow 2

  • Lightweight and fast with a transparent and pythonic API

  • Strive on large datasets: 🤗 Datasets naturally frees the user from RAM memory limitation, all datasets are memory-mapped on drive by default.

  • Smart caching: never wait for your data to process several times

  • 🤗 Datasets currently provides access to ~1,000 datasets and ~30 evaluation metrics and is designed to let the community easily add and share new datasets and evaluation metrics. You can browse the full set of datasets with the live 🤗 Datasets viewer.

🤗 Datasets originated from a fork of the awesome TensorFlow Datasets and the HuggingFace team want to deeply thank the TensorFlow Datasets team for building this amazing library. More details on the differences between 🤗 Datasets and tfds can be found in the section Main differences between 🤗 Datasets and tfds.

Contents

The documentation is organized in six parts:

  • GET STARTED contains a quick tour and the installation instructions.

  • USING DATASETS contains general tutorials on how to use and contribute to the datasets in the library.

  • USING METRICS contains general tutorials on how to use and contribute to the metrics in the library.

  • ADDING NEW DATASETS/METRICS explains how to create your own dataset or metric loading script.

  • ADVANCED GUIDES contains more advanced guides that are more specific to a part of the library.

  • PACKAGE REFERENCE contains the documentation of each public class and function.